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Nvidia's memory costs soar 485%, latest AI systems now cost $7.8 million to build -- memory now comprises 25% of the total cost, Rubin GPUs a mere $50,000 apiece
As prices of components are increasing rapidly due to high demand from the AI sector, the cost of these machines is also increasing significantly. Morgan Stanley Research estimates that a next-generation Vera Rubin-based VR200 NVL72 rack will cost major hyperscale cloud service providers (CSPs) around $7.8 million per unit (via @Aaronwei3n), which is tangibly more than about $4 million per GB300 NVL72. Furthermore, because every VR200 NVL72 rack packs plenty of DRAM and NAND, memory now accounts for around 25% of the total cost. Nvidia plans to charge $55,000 per Rubin GPU and $5,000 per Vera CPU when selling them in volume inside VR200 NVL72 chassis to hyperscalers, according to Morgan Stanley. Although the upcoming VR200 NVL72 racks use the already familiar Oberon chassis, they use more sophisticated switching, networking, printed circuit board (PCB), cooling, power supply, and even chip packaging components, which increases bill-of-material (BOM) costs and eventually the price of the systems. As a result, each VR200 NVL72 will cost hyperscalers around $7.8 million, according to Morgan Stanley, which is higher than around $7 million we were told by one of our sources in late March. Meanwhile, the cost of memory within a VR200 NVL72 rack will be about $2 million, up 435% from the memory cost in GB300 NVL72, according to the same figures. There are several reasons why the cost of memory is expected to account for 25% of the cost of a VR200 NVL72 system and why the system carries $2 million worth of memory. First up, each of such racks now contains 54 TB of LPDDR5X memory, up from 17 TB of LPDDR5X in the case of a GB200 NVL72, a threefold increase. SemiAnalysis estimates that Nvidia paid $8 per GB per GB of LPDDR5X in Q1, though that price may increase as demand rises in the coming quarters, especially if we are talking about SOCAMM2 modules that are expensive to make and test. In any case, even at $8 per GB, each GB200 NVL72 machine carries $136,000 worth of LPDDR5X memory, whereas each VR200 NVL72 system will contain $408,000 worth of LPDDR5X content. If the price rises to $10, we are talking about $540,000 for LPDDR5X alone. Note that even $10 per GB may be an underestimate* as Nvidia adds its own markup. Secondly, each VR200 NVL72 rack carries about $1 million or more of 3D NAND storage, up from virtually zero inside GB200 NVL72. As a result, $2 million of memory content per Vera Rubin NVL72 rack is not something completely unexpected: the system uses a lot of LPDDR5X and 3D NAND memory (not to mention HBM4 memory onboard of Rubin GPUs), and memory now comes at massive prices. *Contract price of DDR5 memory is now between $12 and $16 per GB, depending on various factors and luck, according to Framework. Spot price for DDR5 was about $20 per GB on average at press time, according to DRAMeXchange. LPDDR5X is more expensive than DDR5. When installed on SOCAMM2 modules (which are exclusively used by Nvidia's Vera CPUs), it will get even more costly, especially when Nvidia's markup is added. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.
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NVIDIA's Vera Rubin Rack Hit With 435% Memory Price Surge, Pushing HBM4 & LPDDR5X Bill to $2M of $7.8M Total
NVIDIA's BoM for its upcoming Vera Rubin "NVL72" rack shows a massive surge in memory prices that now make up 26% of the total system cost. Rising Memory Prices & Demand Pushes Memory Costs Up 26% For NVIDIA's Vera Rubin Versus 9% on Grace Blackwell Racks Vera Rubin is in production and is confirmed for first shipments in the third quarter of 2026, followed by volume ramp in the fourth quarter. While NVIDIA cooks up its grandest AI platform to date, the pricing is also going to be grand. Morgan Stanley Research has shared its estimated BoM for NVIDIA's Vera Rubin "VR200" NVL72 rack, which will feature 72 Vera Rubin GPUs, and each tray will house four Rubin GPUs with two Vera CPUs. We'll need to get into the details, which will give you a better understanding of the platform & its cost breakdown. Let's start with the basics: the NVIDIA NVL72 rack is called Oberon and makes use of 72 GPUs. A single Vera Rubin tray houses 4 "Rubin" GPUs and 2 "Vera" CPUs, as mentioned above. Two GPUs and a single CPU are housed on a motherboard, which is called Superchip. There are 36 Superchips on the NVL 72 rack. So that's a total of 72 GPUs and 36 CPUs. Each Rubin GPU houses 288 GB of HBM4 memory, and each Vera CPU comes with 1.5 TB of LPDDR5X memory. For an NVL72 rack, that's 20.7 TB of HBM4 memory and 54 TB of LPDDR5X memory. There is a lot more that goes into Vera Rubin NVL72 racks, such as networking, cooling, power, interconnects, etc. From Morgan Stanley's data, which highlights an "estimated" BoM (Bill of Materials), we can get a better understanding. Starting with the main cost, the Rubin GPU. The Rubin GPUs are expected to cost almost $4 Million, making it the single-most expensive cost within the NVL72 VR200 rack. That's a 57% bump over the Blackwell NVL72 B300 rack, which had the GPU price around $2.5 million. That's $55,000 US per GPU. The second biggest cost is for the memory, which shouldn't be surprising given how constrained the supply is for LPDDR and HBM technologies right now. With Rubin, the memory alone sees a bump of 435%, jumping from $373,939 in Grace Blackwell to over $2 Million on the Vera Rubin platform. The memory price is combined for both LPDDR5X and HBM4. The Vera CPUs amount to $180,000 of the total cost, which puts each chip at roughly $5000 US. All three combined, the total cost of the rack ends up at $6.14 million. The remaining ~$2 million costs include the NVLink Switches, Networking chips, cooling, power supply, PCB, ABF substrates, MLCC, and additional components. The PCB sees the second-highest bump of 233%, going up from $35,100 in Blackwell to $116,730 on Rubin. NVIDIA's upcoming Vera Rubin NVL72 rack marks a powerful new chapter in AI infrastructure, with a total estimated BOM of $7.8 million, driven largely by a 57% jump in GPU costs and a dramatic 435% surge in memory expenses. Memory now accounts for 26% of the entire system cost, highlighting the intense supply constraints and soaring demand for HBM4 and LPDDR5X. As production ramps for Q3 2026 shipments, Vera Rubin is poised to deliver unprecedented performance at a grand price, reinforcing NVIDIA's dominance while underscoring the rising cost of pushing the frontiers of AI. Follow Wccftech on Google to get more of our news coverage in your feeds.
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Nvidia's next-generation Vera Rubin AI systems will cost hyperscalers $7.8 million per rack, nearly double the previous generation. Memory costs have exploded by 435%, now accounting for 25% of the total bill at $2 million per system. The surge is driven by massive increases in LPDDR5X and HBM4 memory requirements, with each rack packing 54 TB of LPDDR5X and 20.7 TB of HBM4.
Nvidia's upcoming Vera Rubin-based VR200 NVL72 rack will cost major hyperscale cloud service providers around $7.8 million per unit, according to Morgan Stanley Research estimates
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. This represents a significant increase from the approximately $4 million price tag for the current GB300 NVL72 generation. The dramatic escalation reflects broader pressures within the AI sector, where component demand has pushed prices skyward. For organizations investing in next-generation AI systems, this near-doubling of infrastructure costs signals a fundamental shift in capital requirements for maintaining competitive AI capabilities.
Source: Wccftech
The most striking aspect of the Vera Rubin NVL72 AI rack pricing is the explosive growth in memory costs. Memory expenses have surged 435% compared to the GB300 NVL72, jumping from approximately $373,939 to over $2 million per system
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. This means memory now comprises roughly 25% to 26% of the total Bill of Materials, up from just 9% in the previous Grace Blackwell generation1
. The shift fundamentally alters the economics of advanced AI infrastructure, with memory becoming nearly as significant a cost factor as the processors themselves.The rising cost of advanced AI infrastructure stems from massive increases in memory capacity requirements. Each VR200 NVL72 rack contains 54 TB of LPDDR5X memory, a threefold increase from the 17 TB found in GB200 NVL72 systems
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. Additionally, each rack houses 20.7 TB of HBM4 memory across 72 Rubin GPUs, with each GPU containing 288 GB2
. At current pricing estimates of $8 per GB for LPDDR5X, the system carries approximately $408,000 worth of LPDDR5X alone, though prices could climb to $10 per GB or higher as demand intensifies1
. The addition of approximately $1 million worth of 3D NAND storage per rack, up from virtually zero in GB200 systems, further compounds memory expenses1
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While memory steals the spotlight, GPU costs remain the largest single expense within the Vera Rubin NVL72 AI rack. Nvidia plans to charge $55,000 per Rubin GPU when selling in volume to hyperscalers, with the 72 GPUs per rack totaling approximately $4 million
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. This represents a 57% increase over Blackwell's GPU pricing. Each rack also includes 36 Vera CPUs at $5,000 apiece, contributing $180,000 to the total cost2
. The system architecture features 36 Superchips, with each housing two Rubin GPUs and one Vera CPU on a single motherboard. Beyond processors and memory, the remaining approximately $2 million covers increasingly sophisticated switching, networking, printed circuit board components, cooling, power supply, and chip packaging1
. Notably, PCB costs jumped 233%, climbing from $35,100 in Blackwell to $116,730 in Rubin2
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Source: Tom's Hardware
The memory price surge reflects intense supply constraints affecting both HBM4 and LPDDR5X technologies. Contract prices for DDR5 memory now range between $12 and $16 per GB, with spot prices averaging around $20 per GB, and LPDDR5X commands even higher premiums
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. The specialized SOCAMM2 modules used exclusively by Nvidia's Vera CPUs add further cost complexity due to expensive manufacturing and testing requirements. With Vera Rubin confirmed for first shipments in Q3 2026 and volume production ramping in Q4 2026, hyperscalers face difficult decisions about capital allocation2
. The escalating costs may force some organizations to extend the lifespan of current-generation systems or pursue alternative architectures. Meanwhile, memory manufacturers stand to benefit substantially from sustained high pricing, though any supply expansion could moderate prices in late 2026 or 2027. For now, organizations building large-scale AI infrastructure must prepare for significantly higher capital expenditures, with memory becoming a critical cost management focus alongside traditional processor expenses.Summarized by
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